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New Truck Models. National Capital Region TPB Travel Forecasting Subcommittee William G. Allen, Jr., P.E. Transportation Planning Consultant 18 July 2008. Timeline. Feb. 04 – Apr. 07: COM model developed 18 May 2007: COM presentation to TFS May 2007: truck models started

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new truck models
New Truck Models

National Capital Region TPB

Travel Forecasting Subcommittee

William G. Allen, Jr., P.E.

Transportation Planning Consultant

18 July 2008

timeline
Timeline
  • Feb. 04 – Apr. 07: COM model developed
  • 18 May 2007: COM presentation to TFS
  • May 2007: truck models started
  • Jan. 2008: truck models completed
  • Jan. – Jul. 08: TPB truck model testing
  • 23 May 2008: TPB truck presentation to TFS
vehicle types
Vehicle Types
  • Commercial: Light-duty vehicle (car, van, pickup) used for non-personal transportation
  • Medium Truck: 2 axles, 6 tires (FHWA class 5)
  • Heavy Truck: 3+ axles (FHWA classes 4 and 6-13)
    • Includes Buses
definitions
Definitions
  • Heavy Truck: 3+ axles, more than 6 tires
  • Medium Truck: 2 axle, 6 tires
  • Commercial: light duty vehicles used for business
truck model history
Truck model history
  • Original model developed from 1968 truck O-D survey
  • Original truck types: light, medium, heavy
  • Models updated in 1985, based on limited count data and 1968 survey
a new approach
A new approach
  • Truck surveys don’t work
  • Use new method developed for COM model
  • Trip-based method consistent with current modelling procedures
  • Borrow a starting model
  • Use counts to synthesize more counts
  • Use counts to adjust starting trips
  • Use trip difference to refine the starting model
  • Same method used for BMC, ARC, Ohio DOT
truck counts
Truck Counts
  • Primary data source: MDOT counts
    • 6 permanent counts
    • 315 short-term counts
  • Secondary data sources:
    • DC classification counts (11)
    • Virginia classification counts (33)
    • TPB 4-hour class. counts (148)
    • (2003) TPB External Truck Survey (10 sites)
daily truck count statistics
Daily truck count statistics
  • Truck percentage: MTK=3.3%, HTK=3.2%
  • TRK % range: 0.9% to 26.1% (US 1 in Jessup, MD)
  • TRK vol. range: 27 – 14,700 (I-95, Howard Co.)
  • Approx. TOD split: 19% AM, 14% PM, 67% OP
synthesized counts
Synthesized Counts
  • Model % HTK, % MTK by link using count data
  • Logit function: % TRK = 1 / (1 + eU)
  • U  lanes, facility type, area type, jurisdiction
  • Apply to all links with counts
  • TRK “count” = est % TRK * count
  • Thorough manual review
  • Use actual counts where available
trk analysis findings
% TRK analysis findings
  • Synthesizing counts provides data for DC and VA
  • % TRK goes up with:
    • Less developed areas
    • Higher facility types
    • Increasing lanes (MTK); decreasing lanes (HTK)
borrow a starting model
Borrow a starting model
  • Simple linear regression model, from BMC model
  • Based on employment by type (industrial, office, retail, other) and HHs
  • Adjustments for area type, truck zone
  • F’s from BMC and Quick Response Freight Manual
  • TOD percentages from MDOT count data
truck zones
Truck Zones
  • Zones with identifiable truck generators
  • Business districts, warehouses, manufacturing, transfer, airport, delivery
  • 1/0 flag
  • 35 zones identified
  • 3-5 times higher truck trip rate per job
model statistics
Model Statistics
  • Retail, Industrial empl are most important
  • Higher trip rate (per empl) in less developed areas
  • External share  distance from cordon
  • 2005 trip totals: MTK=474 K, HTK=192 K, total=666 K
  • Avg. trip length: MTK=24 min., HTK=58 min., total=34 min.
  • Prior model: 553K trips, 43 min. avg
adaptable assignment
“Adaptable Assignment”

Starting

model

Starting

trip table

Assign

trips

Repeat

(7 iter.)

Skim loads

& counts

Final

trip table

Adjust

trips

Delta

trip table

Inform

delta analysis
Delta analysis
  • Subtract starting trips from new trips
  • Analyze trip end summary of difference
  • Correlate with HH, employment
  • Use to inform model (revise coeffs.)
  • Keep “delta” table as adjustment
calibration adjustment
Calibration adjustment
  • O/D table of mostly small adjustments
  • Accounts for random error in assignment
  • Table totals: MTK=7.8 K, HTK=25.7 K
  • Tend to be short trips; no other pattern
  • Carried along for forecasting, added to model’s starting trip table
validation results 2005
Validation results (2005)
  • Prior model (v2.1D, fall 2005)
    • % RMSE: 104%, volume/count: 1.16
    • 553 K trips
  • Starting model
    • % RMSE: 111%, volume/count: 1.33
    • 632 K trips
  • Final model
    • % RMSE: 51%, volume/count: 1.07
    • 666 K trips
more results
More results
  • 2005 VMT
    • Current: 11.4 M
    • New: 10.8 M (-5%)
    • Trips go up, average length goes down
  • 2030 estimate
    • Trips: 916 K (+38%)
    • VMT: 17.3 M (+60%)
conclusions
Conclusions
  • TPB wanted a cost-effective, practical, proven approach
  • Goods movement approach not ready
  • Truck trips are complex -- not suited to an aggregate four-step approach
  • Truck travel is related to national policy and macroeconomic factors beyond our knowledge
  • Don’t wait 20 years to revisit the truck models